Describing Quasi-Graphic Matroids
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On Excluded Minors and Biased Graph Representations of Frame Matroids
On excluded minors and biased graph representations of frame matroids by Daryl Funk M.Sc., University of Victoria, 2009 B.Sc., Simon Fraser University, 1992 Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in the Department of Mathematics Faculty of Science c Daryl Funk 2015 SIMON FRASER UNIVERSITY Spring 2015 All rights reserved. However, in accordance with the Copyright Act of Canada, this work may be reproduced without authorization under the conditions for \Fair Dealing." Therefore, limited reproduction of this work for the purposes of private study, research, criticism, review and news reporting is likely to be in accordance with the law, particularly if cited appropriately. APPROVAL Name: Daryl Funk Degree: Doctor of Philosophy (Mathematics) Title of Thesis: On excluded minors and biased graph representations of frame matroids Examining Committee: Dr. Jonathan Jedwab, Chair Professor, Department of Mathematics Dr. Matthew DeVos Senior Supervisor Associate Professor, Department of Mathematics Dr. Luis Goddyn Co-Supervisor Professor, Department of Mathematics Dr. Bojan Mohar Internal Examiner Professor, Department of Mathematics Dr. Daniel Slilaty External Examiner Professor, Department of Department of Mathematics and Statistics Wright State University Date Defended: 8 January 2015 ii Partial Copyright Licence iii ABSTRACT A biased graph is a graph in which every cycle has been given a bias, either balanced or un- balanced. Biased graphs provide representations for an important class of matroids, the frame matroids. As with graphs, we may take minors of biased graphs and of matroids, and a family of biased graphs or matroids is minor-closed if it contains every minor of every member of the family. -
Math 7410 Graph Theory
Math 7410 Graph Theory Bogdan Oporowski Department of Mathematics Louisiana State University April 14, 2021 Definition of a graph Definition 1.1 A graph G is a triple (V,E, I) where ◮ V (or V (G)) is a finite set whose elements are called vertices; ◮ E (or E(G)) is a finite set disjoint from V whose elements are called edges; and ◮ I, called the incidence relation, is a subset of V E in which each edge is × in relation with exactly one or two vertices. v2 e1 v1 Example 1.2 ◮ V = v1, v2, v3, v4 e5 { } e2 e4 ◮ E = e1,e2,e3,e4,e5,e6,e7 { } e6 ◮ I = (v1,e1), (v1,e4), (v1,e5), (v1,e6), { v4 (v2,e1), (v2,e2), (v3,e2), (v3,e3), (v3,e5), e7 v3 e3 (v3,e6), (v4,e3), (v4,e4), (v4,e7) } Simple graphs Definition 1.3 ◮ Edges incident with just one vertex are loops. ◮ Edges incident with the same pair of vertices are parallel. ◮ Graphs with no parallel edges and no loops are called simple. v2 e1 v1 e5 e2 e4 e6 v4 e7 v3 e3 Edges of a simple graph can be described as v e1 v 2 1 two-element subsets of the vertex set. Example 1.4 e5 e2 e4 E = v1, v2 , v2, v3 , v3, v4 , e6 {{ } { } { } v1, v4 , v1, v3 . v4 { } { }} v e7 3 e3 Note 1.5 Graph Terminology Definition 1.6 ◮ The graph G is empty if V = , and is trivial if E = . ∅ ∅ ◮ The cardinality of the vertex-set of a graph G is called the order of G and denoted G . -
Projective Planarity of Matroids of 3-Nets and Biased Graphs
AUSTRALASIAN JOURNAL OF COMBINATORICS Volume 76(2) (2020), Pages 299–338 Projective planarity of matroids of 3-nets and biased graphs Rigoberto Florez´ ∗ Deptartment of Mathematical Sciences, The Citadel Charleston, South Carolina 29409 U.S.A. [email protected] Thomas Zaslavsky† Department of Mathematical Sciences, Binghamton University Binghamton, New York 13902-6000 U.S.A. [email protected] Abstract A biased graph is a graph with a class of selected circles (“cycles”, “cir- cuits”), called “balanced”, such that no theta subgraph contains exactly two balanced circles. A 3-node biased graph is equivalent to an abstract partial 3-net. We work in terms of a special kind of 3-node biased graph called a biased expansion of a triangle. Our results apply to all finite 3-node biased graphs because, as we prove, every such biased graph is a subgraph of a finite biased expansion of a triangle. A biased expansion of a triangle is equivalent to a 3-net, which, in turn, is equivalent to an isostrophe class of quasigroups. A biased graph has two natural matroids, the frame matroid and the lift matroid. A classical question in matroid theory is whether a matroid can be embedded in a projective geometry. There is no known general answer, but for matroids of biased graphs it is possible to give algebraic criteria. Zaslavsky has previously given such criteria for embeddability of biased-graphic matroids in Desarguesian projective spaces; in this paper we establish criteria for the remaining case, that is, embeddability in an arbitrary projective plane that is not necessarily Desarguesian. -
Ear Decomposition of Factor-Critical Graphs and Number of Maximum Matchings ∗
Ear Decomposition of Factor-critical Graphs and Number of Maximum Matchings ¤ Yan Liu, Shenlin Zhang Department of Mathematics, South China Normal University, Guangzhou, 510631, P.R. China Abstract A connected graph G is said to be factor-critical if G ¡ v has a perfect matching for every vertex v of G. Lov´asz proved that every factor-critical graph has an ear decomposition. In this paper, the ear decomposition of the factor-critical graphs G satisfying that G ¡ v has a unique perfect matching for any vertex v of G with degree at least 3 is characterized. From this, the number of maximum matchings of factor-critical graphs with the special ear decomposition is obtained. Key words maximum matching; factor-critical graph; ear decomposition 1 Introduction and terminology First, we give some notation and definitions. For details, see [1] and [2]. Let G be a simple graph. An edge subset M ⊆ E(G) is a matching of G if no two edges in M are incident with a common vertex. A matching M of G is a perfect matching if every vertex of G is incident with an edge in M. A matching M of G is a maximum matching if jM 0j · jMj for any matching M 0 of G. Let v be a vertex of G. The degree of v in G is denoted by dG(v) and ±(G) =minfdG(v) j v 2 V (G)g. Let P = u1u2 ¢ ¢ ¢ uk be a path and 1 · s · t · k. Then usus+1 ¢ ¢ ¢ ut is said to be a subpath of P , denoted by P (us; ut). -
Associated Primes of Powers of Edge Ideals and Ear Decompositions Of
ASSOCIATED PRIMES OF POWERS OF EDGE IDEALS AND EAR DECOMPOSITIONS OF GRAPHS HA MINH LAM AND NGO VIET TRUNG Abstract. In this paper, we give a complete description of the associated primes of every power of the edge ideal in terms of generalized ear decompo- sitions of the graph. This result establishes a surprising relationship between two seemingly unrelated notions of Commutative Algebra and Combinatorics. It covers all previous major results in this topic and has several interesting consequences. Introduction This work is motivated by the asymptotic properties of powers of a graded ideal Q in a graded algebra S over a field. It is known that for t sufficiently large, the depth of S/Qt is a constant [3] and the Castelnuovo-Mumford regularity of Qt is a linear function [6], [24]. These results have led to recent works on the behavior of the whole functions depth S/Qt [16] and reg Qt [9], [10]. Inevitably, one has to address the problem of estimating depth S/Qt and reg Qt for initial values of t. This problem is hard because there is no general approach to study a particular power Qt. In order to understand the general case one has to study ideals with additional structures. Let R = k[x1, ..., xn] be a polynomial ring over a field k. Given a hypergraph Γ on the vertex set V = {1, ..., n}, one calls the ideal I generated by the monomials Qi∈F xi, where F is an edge of Γ, the edge ideal of Γ. This notion has provided a fertile ground to study powers of ideals because of its link to combinatorics (see e.g. -
Oriented Hypergraphs: Introduction and Balance
Oriented Hypergraphs: Introduction and Balance Lucas J. Rusnak Department of Mathematics Texas State University San Marcos, Texas, U.S.A. [email protected] Submitted: Oct 1, 2012; Accepted: Sep 13, 2013; Published: Sep 26, 2013 Mathematics Subject Classifications: 05C22, 05C65, 05C75 Abstract An oriented hypergraph is an oriented incidence structure that extends the con- cept of a signed graph. We introduce hypergraphic structures and techniques central to the extension of the circuit classification of signed graphs to oriented hypergraphs. Oriented hypergraphs are further decomposed into three families – balanced, bal- anceable, and unbalanceable – and we obtain a complete classification of the bal- anced circuits of oriented hypergraphs. Keywords: Oriented hypergraph; balanced hypergraph; balanced matrix; signed hypergraph 1 Introduction Oriented hypergraphs have recently appeared in [8] as an extension of the signed graphic incidence, adjacency, and Laplacian matrices to examine walk counting and provide a combinatorial model for matrix algebra. It is known that the cycle space of a graph is characterized by the dependent columns of its oriented incidence matrix — we further expand the theory of oriented hypergraphs by examining the extension of the cycle space of a graph to oriented hypergraphs. In this paper we divide the problem of structurally classifying minimally dependent columns of incidence matrices into three categories – balanced, balanceable, and unbal- anceable – and introduce new hypergraphic structures to obtain a classification of the minimal dependencies of balanced oriented hypergraphs. The balanceable and unbal- anceable cases will be addressed in future papers. The concept of a balanced matrix plays an important role in combinatorial optimiza- tion and integral programming, for a proper introduction see [3, 4, 10, 14]. -
Ear-Slicing for Matchings in Hypergraphs
Ear-Slicing for Matchings in Hypergraphs Andr´as Seb˝o CNRS, Laboratoire G-SCOP, Univ. Grenoble Alpes December 12, 2019 Abstract We study when a given edge of a factor-critical graph is contained in a matching avoiding exactly one, pregiven vertex of the graph. We then apply the results to always partition the vertex-set of a 3-regular, 3-uniform hypergraph into at most one triangle (hyperedge of size 3) and edges (subsets of size 2 of hyperedges), corresponding to the intuition, and providing new insight to triangle and edge packings of Cornu´ejols’ and Pulleyblank’s. The existence of such a packing can be considered to be a hypergraph variant of Petersen’s theorem on perfect matchings, and leads to a simple proof for a sharpening of Lu’s theorem on antifactors of graphs. 1 Introduction Given a hypergraph H = (V, E), (E ⊆ P(V ), where P(V ) is the power-set of V ) we will call the elements of V vertices, and those of E hyperedges, n := |V |. We say that a hypergraph is k- uniform if all of its hyperedges have k elements, and it is k-regular if all of its vertices are contained in k hyperedges. Hyperedges may be present with multiplicicities, for instance the hypergraph H = (V, E) with V = {a, b, c} consisting of the hyperedge {a, b, c} with multiplicity 3 is a 3-uniform, 3-regular hypergraph. The hereditary closure of the hypergraph H = (V, E) is Hh = (V, Eh) where Eh := {X ⊆ e : e ∈ E}, and H is hereditary, if Hh = H. -
Circuit and Bond Polytopes on Series-Parallel Graphs$
Circuit and bond polytopes on series-parallel graphsI Sylvie Bornea, Pierre Fouilhouxb, Roland Grappea,∗, Mathieu Lacroixa, Pierre Pesneauc aUniversit´eParis 13, Sorbonne Paris Cit´e,LIPN, CNRS, (UMR 7030), F-93430, Villetaneuse, France. bSorbonne Universit´es,Universit´ePierre et Marie Curie, Laboratoire LIP6 UMR 7606, 4 place Jussieu 75005 Paris, France. cUniversity of Bordeaux, IMB UMR 5251, INRIA Bordeaux - Sud-Ouest, 351 Cours de la lib´eration, 33405 Talence, France. Abstract In this paper, we describe the circuit polytope on series-parallel graphs. We first show the existence of a compact ex- tended formulation. Though not being explicit, its construction process helps us to inductively provide the description in the original space. As a consequence, using the link between bonds and circuits in planar graphs, we also describe the bond polytope on series-parallel graphs. Keywords: Circuit polytope, series-parallel graph, extended formulation, bond polytope. In an undirected graph, a circuit is a subset of edges inducing a connected subgraph in which every vertex has degree two. In the literature, a circuit is sometimes called simple cycle. Given a graph and costs on its edges, the circuit problem consists in finding a circuit of maximum cost. This problem is already NP-hard in planar graphs [16], yet some polynomial cases are known, for instance when the costs are non-positive. Although characterizing a polytope corresponding to an NP-hard problem is unlikely, a partial description may be sufficient to develop an efficient polyhedral approach. Concerning the circuit polytope, which is the convex hull of the (edge-)incidence vectors of the circuits of the graph, facets have been exhibited by Bauer [4] and Coulard and Pulleyblank [10], and the cone has been characterized by Seymour [23]. -
3-Flows with Large Support Arxiv:1701.07386V2 [Math.CO]
3-Flows with Large Support Matt DeVos∗ Jessica McDonald† Irene Pivotto‡ Edita Rollov´a§ Robert S´amalˇ ¶ Abstract We prove that every 3-edge-connected graph G has a 3-flow φ with 5 the property that supp(φ) 6 E(G) . The graph K4 demonstrates 5 j j ≥ j j 5 that this 6 ratio is best possible; there is an infinite family where 6 is tight. arXiv:1701.07386v2 [math.CO] 18 Feb 2021 ∗Department of Mathematics, Simon Fraser University, Burnaby, B.C., Canada V5A 1S6, [email protected]. †Department of Mathematics and Statistics, Auburn University, Auburn, AL, USA 36849, [email protected]. ‡School of Mathematics and Statistics, University of Western Australia, Perth, WA, Aus- tralia 6009, [email protected]. §European Centre of Excellence, NTIS- New Technologies for Information Society, Faculty of Applied Sciences, University of West Bohemia, Pilsen, [email protected]. ¶Computer Science Institute of Charles University, Prague, [email protected]ff.cuni.cz. 1 Contents 1 Introduction 3 2 Flow and Colouring Bounds 7 3 Ears 9 3.1 Ear Decomposition . 9 3.2 Weighted Graphs and Ear Labellings . 10 4 Setup 12 4.1 Framework . 13 4.2 Minimal Counterexample . 14 4.3 Contraction . 15 4.4 Deletion . 17 4.5 Pushing a 3-Edge Cut . 18 4.6 Creating G• ............................. 20 5 Forbidden Configurations 23 5.1 Endpoint Patterns . 25 5.2 Forbidden Configurations . 26 6 Taming Triangles 30 6.1 The Graph G∆ ........................... 32 6.2 Type 222 and 112 Triangles . 35 7 Cycles and Edge-Cuts of Size Four 37 7.1 Removing Adjacent Vertices of G∆ . -
Varieties of Combinatorial Geometries by J
transactions of the american mathematical society Volume 271, Number 2, June 1982 VARIETIES OF COMBINATORIAL GEOMETRIES BY J. KAHN1 AND J. P. S. KUNG Abstract. A hereditary class of (finite combinatorial) geometries is a collection of geometries which is closed under taking minors and direct sums. A sequence of universal models for a hereditary class 'S of geometries is a sequence (T„ ) of geometries in ?T with rank Tn = n, and satisfying the universal property: if G is a geometry in 5" of rank n, then G is a subgeometry of T„. A variety of geometries is a hereditary class with a sequence of universal models. We prove that, apart from two degenerate cases, the only varieties of combina- torial geometries are ( 1) the variety of free geometries, (2) the variety of geometries coordinatizable over a fixed finite field, and (3) the variety of voltage-graphic geometries with voltages in a fixed finite group. 1. Introduction. The notion of free objects in a variety is one of the most important and pervasive ideas in universal algebra. In this paper, we investigate how that notion can be interpreted in the context of the theory of combinatorial geometries (or matroids). No detailed knowledge of universal algebra is required for reading this paper. However, we do assume familiarity with the basic concepts of the theory of combinatorial geometries [2, 4 and 13]. To fix our terminology, let G be a finite geometric lattice. Its maximum and minimum are denoted by 1 and 0. Let S be the set of points (or atoms) in G. -
Chapter 5 Connectivity
Chapter 5 Connectivity 5.1 Introduction The (strong) connectivity corresponds to the fact that a (directed) (u,v)-path exists for any pair of vertices u and v. However, imagine that the graphs models a network, for example the vertices correspond to computers and edges to links between them. An important issue is that the connectivity remains even if some computers and links fail. This will be measured by the notion of k-connectivity. Let G be a graph. Let W be an set of edges (resp. of vertices). If G W (resp. G W) is not \ − connected, then W separates G, and W is called an edge-separator (resp. vertex-separator) or simply separator of G. For any k 1, G is k-connected if it has order at least k + 1 and no set of k 1 vertices ≥ − is a separator. In particular, the complete graph Kk+1 is the only k-connected graph with k + 1 vertices. The connectivity of G, denoted by κ(G), is the maximum integer k such that G is k-connected. Similarly, a graph is k-edge connected if it has at least two vertices and no set of k 1 edges is a separator. The edge-connectivity of G, denoted by κ (G), is the maximum − integer k such that G is k-edge-connected. For any vertex x, if S is a vertex-separator of G x then S x is a vertex-separator of G, − ∪{ } hence κ(G) κ(G x)+1. ≤ − However, the connecivity of G x may not be upper bounded by a function of κ(G); see Exer- − cise 5.3 (ii). -
The Atomic Decomposition of Strongly Connected Graphs
The atomic decomposition of strongly connected graphs Bruno Courcelle LaBRI, Bordeaux University and CNRS Email : [email protected] July 2, 2013 Abstract We define and study a new canonical decomposition of strongly con- nected graphs that we call the atomic decomposition. We can construct it in linear time from the decomposition in 3-connected components of the considered graph. In a companion article, we use it to characterize, up to homeomorphism, all closed curves in the plane having a given Gauss word. 1 Introduction There are many types of hierarchical graph decompositions. They are useful for studying the structure and properties of certain graphs and for building efficient graph algorithms. These algorithms exploit the tree structure of the considered decomposition of the input graph. Here are some examples. The modular decom- position [MoRad] (also called substitution decomposition) has been introduced by Gallai [Gal] for studying comparability graphs and their transitive orienta- tions. The split decomposition introduced by Cunnigham [Cun] (its definition is in Section 4) helps to understand and recognize circle graphs [Cou08, GPTCb]. Tree-decompositions are essential for the proof by Robertson and Seymour of the Graph Minor Theorem (see [Die] for an overview). They yield the notion of tree-width, an integer graph invariant that can be used as parameter in many fixed parameter tractable (FPT) algorithms (see the books [CouEng, DF, FG]). Clique-width is another integer graph invariant based on hierchical decomposi- tions, that can also be used as parameter in FPT algorithms [CouEng, CMR]. Each type of decomposition is based on a set of elementary graphs and of oper- ations on graphs.